bc6e5bcde4
v_head_fwd now reads V_MIN/V_MAX from ISV slots 485/484 (same slots the C51 atom support adapter writes) and clamps the linear output to that range at the kernel boundary. Bounds advantage magnitude (|returns − V_pred|) by 2 × V_MAX regardless of stale-V state. Defensive fix per pearl_clamp_v_target_at_atom_span + pearl_c51_atom_span_must_track_clamp_range — protects against the canonical reward_scale↔V-head response-time pathology where V's stale predictions amplify into PPO surrogate + V regression spikes when the controller adapts reward_scale aggressively. In the F.5 200-step local smoke this clamp didn't bite (V_pred stayed within bounds at the short run length), but the structural protection matters for longer production runs where V can drift before the controllers catch up. Hard-saturated clamp (no straight-through estimator) — the gradient at the boundary is zero in the "push further out" direction, normal toward the interior. V can always learn back into bounds when its raw output drifts out (target is inside bounds → grad pulls V back in), but cannot push the prediction outside support. API surface change: `ValueHead::forward(h_t, b_size, v_pred)` → `ValueHead::forward(h_t, isv, b_size, v_pred)`. The 3 call sites in IntegratedTrainer (step_synthetic + step_with_lobsim h_t/h_tp1) now pass `&self.isv_d`. Verification (RTX 3050 Ti): * cargo check -p ml-alpha → clean * integrated_trainer_smoke 1/1 → ok * frd_head 10/10 + trade_management_kernels 5/5 → no regression * audit-rust-consts → 0 flags Independent finding from the smoke diag: the OBSERVED chronic spike pattern (|l_pi|>30, l_v>100) traces to `rl_reward_clamp_controller` widening WIN/LOSS bounds to 41.3 (vs seeds 1.0/3.0) when MARGIN hits its MAX_MARGIN=5 ceiling. That's a separate failure mode addressed in the next commit (structural cap on scaled reward magnitude).
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.