f50a974fb613ed995a4858360bc63658117fadeb
H1 result (commit9adbca826, smoke train-5zmkr, reverted ate8814079d): aux_dir_acc HD[2] = 78% with H=200 — aux head LEARNS direction at longer horizon. But policy WR stayed pinned at 50.1-50.2% — the learned aux signal does NOT propagate to policy (per pearl_separate_aux_trunk_when_shared_starves: aux on separate trunk with stop-grad to policy). H6 design (synthesized from all v5-v11 + H1 evidence): Wire the aux head's directional probability into the policy STATE as an input feature. - Policy gradient flows THROUGH the feature (uses it) - Stop-grad blocks gradient BACK (aux trunk unaffected, pearl preserved) - Uses existing padding slot [121..128) in STATE_DIM=128 (no layout growth) Why this is the structural fix: - Aux PROVED directional signal is in the features (78% at H=200) - Policy PROVED it can't extract direction (WR=50% across all v5-v11 conditions) - Bridge connects the two without violating trunk separation - Information-theoretic: gives policy a feature it provably can't compute itself Test outcome interpretation: WR > 50.5% → Mechanism 1 was binding (trunk separation gap) WR pinned → Mechanism 2 (reward density) or Mechanism 3 (V/A unidentifiability) dominates → H3 or V/A fix next Files changed: - docs/plans/2026-05-12-sp22-wr-plateau-investigation.md: H6 added as new primary hypothesis after H1; experiment order revised - docs/dqn-wire-up-audit.md: H6 design entry with three-mechanism synthesis Implementation scope (separate commit): 1. State layout: claim slot in padding [121..128) for aux_dir_prob 2. Aux trunk export: pull "up" probability per bar from aux forward 3. Experience collection: write aux_dir_prob into per-bar state 4. Stop-grad verification: confirm policy gradient blocked 5. Trade-open persistence: latch aux_dir_prob for trade duration Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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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
Languages
Rust
88.2%
Cuda
7.7%
Python
1.3%
Shell
1.1%
PLpgSQL
0.8%
Other
0.8%