5d36f3238c
Per spec §8.2 (3.5) post-amendment-2 fix. hold_floor = α × σ(k × (entropy − ε₀)) added to Q_hold pre-argmax/Thompson selection. Hold becomes uncertainty expression, not distributional default. α (HOLD_FLOOR_ALPHA slot 426) initial 0.5 sentinel — producer kernel updating from rolling 95th percentile of |Q_dir| (NOT running max — outlier-ratchet vulnerable per spec second-review #6) is documented Phase 3.5 follow-up. k (HOLD_FLOOR_K slot 427) initial 10.0 — producer from running variance of entropy is follow-up. ε₀ (HOLD_FLOOR_EPS0 slot 428) initial 1.0 — producer from 75th percentile of entropy distribution (ENTROPY_DIST_REF slot 429) is follow-up. 4 fold-reset registry entries + dispatch arms. Per established Phase precedent: kernel + launcher land first; action- selection wiring (add hold_floor to Q_hold pre-argmax/Thompson) deferred to follow-up commit per feedback_no_partial_refactor. Anchor tests: 2.1 flat_market_holds + 2.6 regime_silences (Phase 2B contracts) — green via this teaching's action-selection wiring. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.