1c63c32297
User correctly challenged the "band-aid removal" framing. All fixes shipped during the val-Flat-collapse investigation addressed real bugs at their respective layers and should be preserved: - Kelly cap warm-branch (0c9d1ee39): post-decision physics layer. Thompson-independent. KEEP. - Train Return display + Sharpe annualization (non-tau parts of7a3d88646): display/metric layer. Thompson-independent. KEEP. - Direction Boltzmann tau-floor (tau part of7a3d88646) + adaptive eps_dir floor (d54b49efc): gates inside direction-branch action selection. Phase 2 replaces direction-branch action selection wholesale (eps-greedy + Boltzmann → Thompson), so these direction-only code paths become structurally unreachable. The latter two are NOT band-aids being removed because Thompson is better. They are dead code being cleaned up because Thompson replaces the surrounding mechanism. Magnitude/order/urgency branches keep their existing eps-greedy + Boltzmann + tau-floor + EPS_FLOOR paths intact. Reframed Phase 3 deliverable: "direction-branch dead-code cleanup" with explicit rationale (per feedback_no_legacy_aliases.md and feedback_no_partial_refactor.md). 0.5 day budget instead of 1. Also clarified eval action selection: argmax of (E[Q_C51]+E[Q_IQN])/2 is correct. Bellman backup is a Q-learning UPDATE rule, not an action-selection rule. Once Q is learned, optimal policy is greedy argmax of learned Q. Online Bellman lookahead at eval would require a forward model of market dynamics — not available, not standard. 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.