0e8804a770
Retracts the prior SUPERSEDED footer (commit42ffd6aad). The technical proposal still stands — Thompson sampling on C51+IQN distributions is the canonical action selector for distributional RL (Bellemare 2017, Dabney 2018). Phase 0 tests and the Aggregation Contract are sound math/engineering regardless of the measurement-bug findings. What changed is the URGENCY framing, not the validity. The val-Flat- collapse / Short-collapse observations cited as motivating evidence were partly distorted by three measurement bugs (a86fba2b1+b8788511c) in the diagnostic infrastructure. The "ship Thompson NOW because val_dir_dist collapses to 80%+ Hold/Flat" narrative dissolves; the "Thompson is the principled action selector for our distributional model" narrative stands. Sequencing: PAUSED pending evidence from a fresh L40S 30-epoch baseline (train-f8h6q, 2026-04-27 12:20) on post-fix code. The baseline is a bug-hunting expedition — kill on anomaly, diagnose, fix, re-run per feedback_stop_on_anomaly.md. Once healthy baseline established, Phase 2 ships as principled improvement with clean A/B against the trustworthy post-fix metrics. Plans B / C / D are PAUSED, not cancelled. Files remain in docs/superpowers/plans/. Resumption gate: post-fix baseline run is bug-free or all surfaced bugs are addressed.
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.